Radiology reports are typically written in language well above the average American adult’s eighth grade reading level, making them a source of confusion for patients.
The lead-up to radiation therapy can be anxiety-inducing and painful, but experts are optimistic a new relaxation method that is equal parts ancient and futuristic could help to ease patients’ worries.
The tool uses a machine learning technique to identify changes on brain MRIs that would otherwise be overlooked by radiologists due to the subtlety of alterations.
Trauma patients who present with poor blood flow and suspected abdominal hemorrhage are well served by emergency physicians using AI-augmented FAST imaging.
Surveying the landscape of interpretive AI in radiology, two researchers note a yawning gap between great expectations set in the recent past and actual clinical implementations as of spring 2023.
Out of 10 mock exams, the AI candidate passed two, achieving an overall accuracy of 79.5%, suggesting that the candidate is not quite “ready to graduate.”
A recent analysis found that a significant amount of studies do not provide information pertaining to their raw data, source code or model. As a result, up to 97% of these studies do not produce systems that are fit to be used in real-world clinical scenarios.
Sanjay Parekh, PhD, senior market analyst with Signify Research, explains how some radiology AI is being adopted outside of radiology departments to improve care.
The applications for VR/AR devices are wide-ranging, and could be particularly beneficial in underserved areas where patients have less access to care and clinicians have fewer opportunities to train.
Jorge Soto, MD, chair of the RSNA Annual Meeting Program Planning Committee, chief of radiology, Boston Medical Center, offers an overview of the trends, hot topics, research and technology at the Radiological Society of North America (RSNA) 2022 meeting.
